1. Field
Apparatuses and methods consistent with exemplary embodiments relate to a method, an apparatus, and a recording medium for image stabilization.
2. Description of the Related Art
As an increasing number of people use multimedia devices, demand for image enhancement technology used for digital images captured in various environments is also increasing. The image enhancement technology includes blurring removal, noise removal, image stabilization, and the like, and is widely applied to digital cameras, smart phones, cameras or camcorders for family use, surveillance cameras for industrial use, broadcasting cameras, and image capturing devices such as those for military use. Initially developed image capturing devices produced an image by digitizing an analog image. However, recent image capturing devices produce a high-definition digital image that depicts a subject more clearly than an analog image based on various preprocessing and post processing technologies.
Among digital image correction technologies, image stabilization technology is most commonly used. When a user captures an image while holding an image capturing device or while the user moves to another place, the image capturing device may be shaken. In the case of a camera installed in transportation modes such as a vehicle, an airplane, or a helicopter, the camera may be unintentionally shaken due to many environmental factors such as a mechanical oscillation or friction with the ground. In addition, as a magnification of a zoom lens increases, a screen is severely shaken even though the image capturing device is slightly moved. The image stabilization technology is used to acquire a clear and sharp image even when the image capturing device is shaken while capturing an image, and is applied to remove unwanted effects due to the shaking that are found in the captured image.
Recently, digital image stabilization technology is used to correct shake effects by detecting unwanted shake effects through motion prediction between frames based on input image signals and reading, from a frame memory or a charge-coupled device (CCD), image data of which motions are corrected. Because the digital image stabilization technology may be lower in cost, may have higher accuracy than a mechanical stabilization method, and also compensates for various motion components that cannot be compensated through the mechanical stabilization method, research into the digital image stabilization technology is being actively conducted.
A Kalman filter is a recursive filter that traces a state of signals including noise and is developed by Rudolf Kalman. The Kalman filter is used in various fields such as computer vision, robotics, radar, and the like, and efficiently operates in most cases.
The Kalman filter recursively operates. The Kalman filter is used to estimate a current value based on a value that is estimated immediately before the current value and excludes estimated values and measurement values, other than the value that is estimated immediately before the current value.
An algorithm using the Kalman filter may be divided into two processes: a prediction process and an update (correction) process. First, the prediction process for calculating a state following a state that is previously predicted is performed. Then, the update (correction) process, which is for recursively correcting a calculated prediction state based on an error between the calculated prediction state and an actually measured state and helping more accurately predict a next state, is performed.